applied automation june 2012

A supplement to PLANT ENGINEERINGand Control Engineering magazinesA supplement to PLANT ENGINEERINGand Control Engineering magazines

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Applied Automation June 2012 A3

A4 Understanding process elasticity Lessons learned cooking french fries can teach much about process control strategy. The objective to create a consistent product with minimal operator intervention can apply in many areas.

A8 Optimizing strategy for boiler drum level control Avoid trips and maximize steam output by reviewing your control equipment, strategy, and tuning. A few improvements can bring a significant performance boost.

A12 Challenges of motor selection and sizing The range of sizes, types, and configurations of electric motors can seem endless. Here are a few ideas for navigating the choices.

Contents

A12COMMENT

Does this months cover make your mouth water? Maybe just a little? There arent many situations where we get to do our own food photography, but when an arti-cle is about french fries, I couldnt resist. Perhaps you think the topic is a bit trivial, but according to PotatoPro.com (theres a magazine or website for every industry), consumption of french fries may have declined, but they are still served with more than 13% of restaurant meals, so its dif-ficult to imagine how many deep fryers are in use across the country.

When Chuck Maher offered me this story, I was a little skeptical, but he has written some interesting insights into PID loop tuning (which you can read on his website, www.embededde-signservices.net), so it seemed like an intriguing possibility.

Maybe trying to get a sliver of potato to cook nicely without burning or soaking up too much

fat doesnt seem like a huge challenge, but if you scale up production and you want consistency with minimal waste, the process has to be pretty airtight. McDonalds says it has 33,000 locations around the world, and I imagine pretty much all of them have a fryer or several. Now add in all those others that compete in that arena, and the numbers are mind-boggling.

Moreover, as Maher observes, many of the individuals running those fryers are doing it with little training or experience, so the process has to depend on automation to make up for operators that have too much to do or are unqualified to judge the cooking process. Consequently, having a system that is self-adjusting is paramount. If this sounds a lot like what happens when you put some feedstocks in a reactor and hit go, you get the point.

Think about it the next time you are enticed by the aroma of a fresh batch of fries.

Control strategy of french fries? Are you serious?

Peter WelanderEditor

Time (seconds)

Tem

pera

ture

( deg

rees

F )

Time

EndIdealtime

Fig. 2: Compensated cook curve

Usablerange

DTLLO

DP

LIDrumlevel

transmitter

High

Drum

Saturatedsteam

Water

Water0

level

Low

A4

A8

AAM1206_Contents_V3msFINAL.indd 3 5/29/12 3:06 PM

A4 June 2012 Applied Automation

Understanding Process ElasticityLessons learned cooking french fries can teach much about process control strategy.

Editors note: While this story is specifically about french fries, the same concepts of control strategy apply to many types of processes, particularly batch pro-cesses. For example, the amount of time feedstocks have to spend in a reactor can vary according to all sorts of variables, and an effective control strategy has to be able to measure those variables and com-pensate automatically to ensure the cor-rect outcome. The solutions in this case may help you find your own.

How many times have you stood in line at a McDonalds, Burger King, Wendys, or the like, and listened to a loud cacophony of beeps, buzzes, and other assorted noises that seem to be calling attention to something urgent. They are, of course, alarms of various sorts. Quick-

service restaurants (they seem to prefer this title over fast food) have an ingenious collection of microprocessor-based controllers on all their cooking appliances. They need them to fulfill their corporate goals of consistent food quality and ease of operation due to high a turnover in personnel, and to minimize the number of people needed to staff the restaurant and service customers. These chal-lenges sound like those encountered in many process plants these days.

McDonalds boasts that the french fry (FF) you get in New York City is the same as the one you get in Beijing. This is, for the most part, true because much science and testing has gone into the process of cooking FFs. It may seem trivi-al at first: You take the raw fries out of a package and dump them in hot oil, wait a while, and take them out, right? Its actually a complex process not all that different from many found in various phases of chemical manufacturing.

Consider these questions: What is the best cooking temperature for the oil? How long should you cook a batch? How much does batch size affect the cooking time? Are the potatoes frozen or slacked (defrosted)?

Most people know through either intuition or experience that things cook faster at a higher temperature than at a

lower one, but the product can also burn or become inedible if you go too far.

A mentor once told me, Cooking is all about boiling water. This is true in general and particularly so with deep fat frying. When a batch of FFs is lowered into a vat of hot oil, there is a rapid drop in temperature. Potatoes contain water on the surface and internally that turns to steam, so it is similar to many types of endothermic reactions. It is the latent heat of vaporization absorbed from the hot oil that causes this rapid drop in tem-perature. If the controller cant heat the oil quickly enough to compensate, the

cooking rate slows down.The fryer controller has two primary functions. One is to

control the temperature of the oil, and the other is to time the cooking interval. Both functions are directly related. Legend has it that in the early 1960s when McDonalds was becoming more widely established, company chefs undertook an extensive set of experiments in the test lab where small amounts of FFs were cooked at one-degree temperature intervals. These FFs were then rated as to their degree of doneness.

Determining ideal conditionsA properly cooked FF will be crisp on the outside,

snapping when you bend it. Its center will be pulpy and not dried out. The outside color will be a pleasing brown and, above all, it must taste good. There must not be any unpleasant flavor transmitted from the cooking oil. That is why fryers that cook fish should never be used for cook-ing FFs. The net result of all these tests was a so-called optimum cook curve of time versus temperature for FFs. (See Figure 1.) The lower the temperature, the longer the product had to be cooked, but if the oil temperature stayed too low for too long, then the product was unacceptable. It was undercooked, limp, greasy, and pale in color.

Assume that the resulting curve showed that the opti-mum oil temperature to start a batch cooking is 350 F and that when cooking a small batch of FFs a cook time of 150 sec (2.5 min) produces a very good product. Problem solved? Now lower a basket with 5 lbs of frozen potatoes into the fryer and watch the upheaval.

The oil temperature will plummet in seconds to around 300 F or lower. If you remove the FFs after 2.5 min, theyre garbage. You must lengthen the time based on the

Chuck Maher

PROCESS CONTROL STRATEGY

AAM1206_Feat01_ElasticTime_V3msFINAL.indd 4 5/29/12 2:49 PM

drop in temperature. The same applies to all sorts of chemical reactions where the rate is a function of temperature. This need is referred to by several different names: elastic time, comp time, load compensa-tion, and other similar terms to describe the effect.

In the early to mid-1970s the first micro-processors were still almost a decade away. Electronic cooking controllers were being implemented using a combination of discrete logic (gates and counters) and monolithic analog components (transistors and operational amplifiers). The Fairchild 709 monolithic IC op amp came on the scene in 1965 and was quickly put to use in cooking controllers.

In 1978, U.S. Patent number 4,362,094 was issued, titled Cooking Time Control System. It made use of discrete monolithic components only. There is no microcon-troller and therefore no firmware. It was all hardwired. This patent describes a pulse train that is feeding a counter that has its frequency changed based on a cooking rate.

All about heat flowThe cooking rate is defined as the rate

of heat flow into the product being cooked. This heat flow is known to be a function of the differential temperature between the hot oil and the product being cooked. This rela-tionship is not a linear one. However, the patent states that this nonlinear region can be closely approximated by a constant over a narrow range of oil temperature. The pat-ent specifies using a platinum RTD sensor for this application because of its linearity, accuracy, and stability.

As the temperature drops, the frequency of the pulse train to the counter is lowered, effectively increasing the cooking time since it takes longer to count the predetermined number of puls-es. While not perfect, this technique proved quite effective in improving the quality and consistency of the final prod-uct. This and similar techniques were used until the first microprocessors became available.

We should all be familiar with cook timers around the kitchen. You set the time interval for which you want a product to cook and start it running. It usually starts counting down so that you can see the time remaining. When the count reaches zero, a bell or chime will go off to tell you that the time has elapsed. Another clever engi-neer in this period before the advent of microcontrollers noticed that the cook curve closely resembled that of the

resistance-versus-temperature curve of a negative-slope thermistor. He then used a thermistor to measure the oil temperature and used its value of resistance, which increases as the temperature drops and vice versa to vary the frequency of a pulse train operating a cook timer. In this way he was able to implement the elastic time fea-ture very effectively. With the advent of microcontrollers it became much easier to use things like lookup tables and such to implement the desired cook curve in firmware and to use different algorithms for implementing the elastic time feature.

A very common way to program a timer is to load an internal register (or counter) with a preset number and


Time (seconds)

Tem

pera

ture

( deg

rees

F )

Fig.1: Cook curve

Usablerange

Time (seconds)

Tem

pera

ture

( deg

rees

F )

Time

EndIdealtime

Fig. 2: Compensated cook curve

Usablerange

The ideal cook time reflects the optimum oil temperature and assumes that tem-perature does not fall during the cook. The shaded area represents the accumulat-ed heat flow into the product, which is a function of the differential temperature between the hot oil and the product. The compensated cook curve recognizes that the oil temperature does normally drop until the controller senses the change and turns the heading element on and it begins to rise again. Ultimately, the area below the two curves should be roughly the same.

The cook curve shows that there is a range of usable time and temperature com-binations that will result in an acceptable final product. However if the tempera-ture is too high the outside cooks too fast, and if it is too low, it will not be crisp.



then periodically decrement or increment it and test the result to see if you have reached zero or the desired count. The secret to variable timing is the period of the pulse that is doing the counting up or down.

For example, if your pulse period is 1 sec and if you want to cook for 2.5 min, you would preset the counter to the binary equivalent of 150. If you doubled the period with the same preloaded count, then the cook would last for 5 min.

Every microcontroller has a built-in time tick. This tick may be in microseconds, milliseconds, or in some cases even seconds. It is generally not an integer but rather some non-integer number and requires some type of scal-ing to get it into the units you need. The cook curve can be translated into a table format where the table is entered with a temperature and exited with a count that represents

the time for that interval and at that temperature. The lower the temperature is, then the larger the number and vice versa.

A simpler way to implement elastic time is to realize that if you multiply the ideal cook temperature for a specific product by its ideal cook time, then the result is in effect the energy absorbed during an ideal cook of that product. If the actual oil temperature is measured at a constant interval and continually added to a register, the value in that register will be the actual integrated time/temperature. This number can be compared to that of the ideal cook, and when equal or slightly greater, the cook will be ended.

This approach loads a register with the ideal energy (ideal cook temperature multiplied by the ideal cook time) and then as the batch cooking progresses, it periodically

process control strategy

When I first began learning about controls, the emphasis seemed to be all about making sure the system was as accurate as possible while meeting its dynamic specifications. That is still important, but consider a unique situation that I ran into many years ago. It was in the mid 1990s and I was working on the design of a microcontroller-based product to operate a line of commercial electric and gas-fired deep fat fryers.

The manufacturer was the second largest in the country and did not make its own controllers. The problem grew from the fact that the company wanted a unit with some rather unique features that the current supplier was not willing to provide. The controllers at that time had to be tuned individually to operate with one of 17 different model fryers. This created many logistical problems in the field with interchangeability and replacement parts.

I wracked my brain for quite a while. Clearly some sort of adaptive approach was called for, and it dawned on me that in this particular application, tight temperature control while idling was not a require-ment. Plus or minus a couple of degrees would not adversely affect any products final quality.

I decided to use a forced-limit cycle technique. I would compel the temperature to fluctuate 2 F while idling and in the steady state. This is not too different from the way a common household thermostat works. Almost all fryers operate from a power relay that oper-ates either a sophisticated gas valve or a bank of three-phase electric heaters.

The algorithm I used was unusual. I later received a patent (USP 5,575,194) for it. The technique consists of closing the heat source relay for an adjustable on time when the falling temperature crosses the set-point. The power stays on for a predetermined length

of time and then turns off.It stays off unless the temperature fails to rise back

above the setpoint. If this should happen, then another pulse is initiated and its duration is lengthened by a fixed amount of time. The program periodically mea-sures the slope of the temperature curve. In this way, it can tell if the temperature is rising, falling, or if it has peaked or bottomed out.

Four flags are key to the operation of this control. One is set if the temperature is above the setpoint, another if it is below, a third if it is falling, and the fourth if it is rising. Any time one flag is set, its oppo-site is automatically reset since they are mutually exclusive. In addition to these four flags, the maximum (peak) and the minimum (lowest) values are also deter-mined and saved.

The whole idea of this approach is to establish a fixed minimum to maximum temperature swing and maintain it. As the temperature is falling from its peak, the difference between the maximum and minimum temperatures for the previous cycle is calculated:

If the swing was less than it should be, then the pulse count is incremented.

If it is right on, then no change is made. If it is too wide, then the pulse count is decremented.In this way, the limit cycle band about the setpoint

is maintained while the fryer is idling. Once the con-trolled temperature has peaked it will start to fall. The rate at which it falls is less than the rate at which it rises when the heat has been turned on. The net result of this is an asymmetrical oscillation about the nominal setpoint. Initially a provision was made in the program to gradually adjust the nominal setpoint while in operation in order to make the oscillation symmetric about the nominal setpoint. Subsequent actual opera-tion of the control showed that this was an unneces-

Adaptive control of deep fat fryers



samples and adds the actual tem-perature to a register, thus integrating the temperature as described above. The program then compares the con-tents of this register to that containing the ideal time/temperature, and when the ideal is exceeded, it signals the end of the process.

Figure 2 shows how this works. The crosshatched area at the begin-ning of the cook represents the ideal cook energy, and the unshaded area below the actual temperature curve is the additional energy (cooking time) needed in order for the actual energy to be equal to or slightly greater than that used during an ideal cook. Clearly the cook time has been

stretched.Another interesting fact was that

the same cook curve developed for cooking FFs was equally effec-tive when baking biscuits in an oven. The cook time needed to be stretched based on how many trays of uncooked biscuit dough were present in the oven. The same con-cept can apply to countless chemical

processes and reactions.Chuck Maher is an automation consultant and owner of

PER Associates in Mustang, Okla. www.embededdesign-services.net

http://www.embededdesignservices.net/

sary complication.It was fascinating to watch

this algorithm at work. On average it took about 5 to 10 min for the control to adapt itself to any given fryer and reach an equilibrium state. What was equally interesting was the information con-tained in the resulting tran-sient wave form. The negative slope of the falling tempera-ture is a measure of the rate of heat loss to the environ-ment, and the positive slope is a measure of the heat gain.

Fryers have some interesting needs. The use of solid short-ening, while not as prevalent today as in the past, requires the use of a melt cycle dur-ing start-up. You cannot just turn the heat full on and go. The heat must be pulsed at a rate which will allow the shortening to melt gradually and turn to liquid.

When it has been determined that the melt cycle is over, either by looking at the temperature change or just on the basis of elapsed time, the heat comes full on and stays on until the oil comes up to set-point. Many controllers will measure the saturated rate of heat rise during this phase and compare it to that measured during the previous start. In this way its possible to detect any deterioration in the heat-ing apparatus. Gas valves may need adjusting if for some reason the heat content of the gas supply may have changed. Electrical heating elements can foul or be compromised in other ways. Our adaptive control shut the heat off during the start-up phase at a pro-

grammed number of degrees below the setpoint, and then measured the overshoot. If the overshoot was higher than the value for the maximum overshoot, then the cutoff point was adjusted to a lower value or vice versa.

Cooking appliances using even eight-bit microcon-trollers are not working very hard. Unless there is a lot of external communication going on, there is ample time to perform other tasks such as diagnostic test-ing. For example, the controller described here has a feature where it looks during start-up for the oil tem-perature to stall at 212 F. This is, of course, the boil-ing point of water. Sometimes after a fryer has been cleaned, operators forget to drain the water and add fresh shortening. Careless operators like that have been scalded by the roiling water when they start the fryer without thinking.

Min

On

OffTime

Max

Setpoint

Cooking mediumtemperature

Adjusted idleon setpoint

Heatingelementsignal

If you multiply the ideal cook temperature for a specific

product by its ideal cook time, then the result is in effect the

energy absorbed during an ideal cook of that product.

The asymmetrical oscillations are caused by the difference in heat flow rate between the heating element operating and loss of heat to the surrounding environment.



Optimizing Strategy forBoiler Drum Level ControlAvoid trips and maximize steam output by reviewing your control

equipment, strategy, and tuning.

Inadequate control of drum level in a natural-circulation boiler can cause trips on a frequency ranging from a few times a year to once a day. Each boiler trip gener-ates expenses that can cost from tens-of-thousands to hundreds-of-thousands of dollars depending on the circumstances. Control engineers can substantially improve level control performance by following a struc-tured approach to troubleshooting the boiler drum level control system including reviewing the control equipment, the strategy, and the controller tuning. This approach can

substantially reduce the number of boiler trips, providing a substantial financial benefit.

Drum level control basicsNatural-circulation boilers are

widely used in various chemical processing and related industries. The design principle uses the dif-ference in density between cooler water in the downcomer and the steam/water mixture in the riser to drive the steam/water mixture through the tubes. The boiler drum separates steam from water and contains inventory to accommo-date operational changes. Water enters the riser tube, is heated, and undergoes a transition from a single-phase liquid to a mixture of

saturated liquid and steam. As heat input increases, the proportion of steam vapor in the riser tube increases.

A high-priority challenge to the control engineer is the ability to control the water level in the drum very precisely. When the water level gets too high it can result in water carryover into the superheater or turbine, potentially causing damage or outages in the turbine or boiler. A level that is too low can expose the water tubes where they connect to the drum, causing them to crack or break. A boiler trip interlock is supposed to prevent these types of damage, but boiler trips can take consider-

able time to clear, during which the expensive produc-tion equipment is often forced to sit idle.

Shrinkand swell

The void frac-tion is the per-centage of steam by volume in the riser tube. The

quality is the percentage of steam by weight in the riser tube. As the quality increases, so does the void fraction. Faster changes in the void fraction are seen at lower steam quality and lower steam pressure. Increasing the boiler firing rate increases the void fraction, which in turn pushes water out of the riser tube into the drum, increas-ing the level of the drum. This effect is known as swell. Likewise, reducing the boiler firing rate reduces the void fraction and water flows downward from the drum into the riser tube, reducing the level of the drum. This effect is known as shrink.

If the steam flow out of the boiler increases, the drum pressure will drop and the boiling rate will increase, increasing the void fraction in the tubes and drum. The increase in the void fraction will push water into the drum, causing swell. The inventory of the boiler must be reduced to accommodate the increased void fraction. The opposite effect is seen when the steam flow out of the boiler decreases or when cold feedwater is added to the drum. The resulting reduction in drum pressure causes the boiler level to shrink.

While the control engineer must pay careful attention to shrink and swell in determining the boiler drum level control strategy, he or she may be surprised to find that changes in these factors sometimes have the opposite effect as was expected. For example, an increase in cold feedwater flow would be expected to increase the inven-tory in the boiler and increase the drum level. But in the short term, increasing feedwater flow tends to quench

Andrew W. R. Waite

process control

00

0.2

0.4

0.6

0.8

1.0

20 40 60 80 100Quality, x, % by weight

Void

frac

tion,

3200 psi (22.1 MPa)

3000 psi (20.7 MPa)

2100 psi (14.5 MPa)

1250 psi (8.6 MPa)650 psi (4.14 MPa)

250 psi (1.72 MPa)

14.7 psi (0.1 MPa)

Figure 1: Natural-circulation boiler drum level process.

Figure 2: Steam quality and void fraction.

AAM1206_Feat02_Boiler_V8msFINAL.indd 8 5/29/12 2:52 PM


the boiling in the drum and also potentially in the tubes. As shown in Figure 3, this may result in a temporary drop in the boiler drum level. Eventually the drum level increases due to increasing inventory. On the other hand, a decrease in feedwater flow tends to increase boiling in the drum and tubes. The result is a temporary rise in the boiler drum level. If the feedwater temperature is higher, close to the drum temperature, these effects will be less noticeable and may disappear completely.

Drum level measurement

Naturally, the control engi-neers first step in maintaining drum level control is to ensure accurate boiler drum level measurement. However, this may be complicated by

the fact that the steam drum itself may not be perfectly level. Even at steady state conditions, turbulence in the drum can cause the level to fluctuate. A changing rate of water inflow and steam outflow adds to the potential for measurement error. Measurement of boiler steam drum level using a differential pressure transmitter must take into account the physical properties of the fluid. The drum contains a two-phase mixture of water and steam at satu-ration conditions. The densities of water and steam vary with saturation temperature or pressure. The density of saturated steam above water must be considered, as well as the density of saturated water in the drum. Suppliers of boiler drum level transmitters will provide instructions for calibrating transmitters that take these factors in account.

Understanding response dynamicsTuning the control loops requires an understanding

of the response dynamics. Open-loop step test-ing as shown in Figure 5 can

help provide this understanding. The feedwater valve is stepped while monitoring the response of the feedwater flow, boiler drum level, and steam flow. In the example shown in Figure 6, the feedwater flow does not respond well to changes in the feedwater valve at the points indicated by the red marks. The problem is a sticky valve. The controller cannot be tuned to fix this problem.

FT101

FT101

LT100

LIC100

29003.500

4.125

4.750

5.3756.000

40.65

46.87

53.09

2311-FT.PV-Cascade2304-LT.PV-Cascade

LUC204AB.dat 12/14/2004LUC204AA.dat 12/14/2004

WHB owWHB level

inch

pph

DY= (0.125 inch/Div)

DU= (1.244 pph/Div) Bump 10

2934 2969 3003 3038 3072 3106 3141 3175Secx=(3.438 Sec/Div)

Change in feedwater ow setpoint

Transition period Steady stateoperation-after

Steady stateoperation-before

i

T i SSe

o

900

68.0260.0152.0144.000 1800

Mean=356752 2Sig=7.74e+004 (21.7%)

Mean=55.1361 2Sig=11.13 (20.2%)2699 3599

9000 1800 2699 3599

Sec

Sec

Lbs/Hr

% Open

Var 04 HRFT2100 (HP2 Feed water ow)

Var 03 HRFV2100 (HP2 Feed water value)

060621 1040Tuning Unit2 1040-1140 AM_C09.dat 06/21/2006 10:40

060621 1040Tuning Unit2 1040-1140 AM_C08.dat 06/21/2006 10:40

1% Steps

420093362127304161246196DT

LLO

DP

LIDrumlevel

transmitter

High

Drum

Saturatedsteam

Water

Water0

level

Low

160016.0016.8017.0017.2017.40

26.40

26.60

26.80

1750 1900 2050 2200 2350

0.1% Steps

2500 2650 2800SecdX=(15 Sec/Div)

m3/h

% Bump 01

DY=(0.04 m3/h/Div)

DU=(0.02 %/Div)

Figure 3: An increase in feedwater initially has the opposite of the expected effect due to shrink.

Figure 4: Measuring drum level.

Figure 5: Basic instru-mentation for boiler level drum control showing sensors that should be monitored when performing open-loop step tests

Figure 6: Step test on valve with 4% backlash

Figure 7: Step test on a valve with less than 0.1% backlash.

700

2.0290.976

-0.078-1.131

400 1000

Mean=60.0812 2Sig=4.963 (8.26%)

Mean=0.0309193 2Sig=1.16 (3.75e+003%)1300 1600

700400 1000 1300 1600

Sec

Sec

Inches

% Open Var 06 HRFV1100 (HP1 Feed water value) 060620 1627HRSG1 Tuning FWBumps 02_C08.dat 06/20/2006 16:27

Var 05 HRLC12SC (HP1 Drum level (composite) 060620 1627HRSG1 Tuning FWBumps 02_C05.dat 06/20/2006 16:27

64.0060.6757.3354.00

Figure 8: The drum level shows very good response to the feedwa-ter valve.



Instead, the control valve needs to be fixed. Of course, its not possible to make a control valve that responds perfectly, but it should respond to 0.5% steps or smaller in the controller output. Figure 7 shows a flow control valve that responds well to control signals.

After the feedwater loop is operating correctly, its time for the control engineer to focus on the drum level. The goal is to achieve sharp transitions in the level slope in response to a change in feedwater flow rate because dead time or delay is destabilizing. Figure 8 shows a good example of a response without any delays. The dynamics of the boiler may include dead time that can-not be eliminated, so to maintain stability in this case, the tuning of the controller must be slowed down.

Types of level control systemsSingle-level element control as shown in Figure 9 uses

only the level measurement and the feedwater valve. The controller responds to a proportional signal from the drum level transmitters by generating a proportional output to the boiler feedwater valve when needed. This approach is often used when starting up a boiler and there is no steam flow or when a flowmeter has failed. The drawback of this strategy is that the level is subject to uncontrolled disturbances from the steam header and the feedwater. For example, if the feedwater header pressure rises, the feedwater flow to the boiler also increases. Without

a feedwater control loop, this situation would be uncor-rected until the level changes. In addition, the installed characteristics of the feedwater valve may compromise level control performance over a large operating range.

Two-element level control as shown in Figure 10 adds the steam flow as a feedforward element to the level con-troller output. A steam mass flow rate signal is used to control the feedwater flow so that feedwater demand can be adjusted immediately in response to load changes. The level controller is used to correct any imbalance between the steam mass flow out of and the feedwater mass flow into the drum. This approach delivers more effective drum level control than a single element. It is well suited for use on a single boiler with a single feed-water pump using a constant feedwater pressure. A potential weakness is that the installed characteristics of the feedwater valve may compromise level control perfor-mance over a large operating range. In addition, steam feedforward may need to be characterized when using this approach.

Three-element level control as shown in Figure 11 is the most common boiler drum level control strategy. A feedwater flow loop slave is added to the two-element strategy. Three-element level control linearizes the feed-water flow with respect to the steam flow and the level controller output. The control loop now requests volumet-

process control

FT101

FT101

LT100

LIC100

FT101

FT101

FT101

LT100

LIC100

dX=(5 Sec/Div)900 950800

1311-FT.PV1304-LT.PV

West WHB feedwater owWest WHB level

LUC408AC.dat 12/16/2004LUC408AA.dat 12/16/2004

850 1000 1050 1100 1150 1200Sec

2.000

3.000

4.000

5.000

6.000

50.0046.0042.0038.0034.0030.00

Inch

pph

DY=(0.2 Inch/Div)

DU=(0.8 pph/Div) Bump 01FT101

FT101

LT100

LIC100

Figure 9: Single-element level control.

Figure 11: Three-element level control.

Figure 12a: Open-loop drum level step test.Figure 10: Two-element control.



ric flow change, not just a change in the valve position. This strategy attempts to compensate for changes or disturbances in steam flow and feedwater flow based on the principle that flow in equals flow out. The installed characteristics of the feedwater valve are no longer an issue because the flow controller can compensate. Using this approach, the steam feedforward element can be a simple gain without requiring characterization.

Tuning the control loopThe recommended procedure for level control tuning

is to tune the feedwater flow loop first to ensure that its fast, stable, and does not overshoot. Then the control engineer should perform open-loop tests on the drum level loop, being careful to start small. Evaluate the response for a number of step tests. Figure 12 shows a well-behaved drum level process without any dead time.

The lambda tuning method for controllers usually pro-vides stable control loops. The blue line in Figure 13

shows the response provided by lambda tuning to correct for a disturbance. The lambda value () is the arrest time where the level deviation is maximum and represents 1/6 of the total recovery time. The lambda tuning equation is

TARR is the arrest time, which is equal to lambda. The greater the process dead time, the greater the lambda value that is required.

Feedforward is generally set up to maintain a 1:1 mass relationship between steam flow and feedwater. If both flow meters are set up for the same span in engineering units, e.g., pounds per hour, then the feedforward gain is normally set to 1.0. Also, consider accounting for other input and output flows that consume steam, such as soot blowing and blow down. A dynamic feedforward approach may be more beneficial than a straight gain.

Handling disturbancesVarious types of disturbances can create level control

challenges for the control engineer. For example, Figure 14 shows a disturbance caused by variations in process steam demand. In this particular application, the steam flow disturbance is an inherent part of the process so it cannot be corrected. The three-element drum level con-trol is kept busy reacting to the variations in steam flow to maintain the drum level at a relatively constant value. Substantial variations in the level are seen when the drum level control goes into manual.

If a steam flow increase causes the drum to swell, the level will increase but the feedforward signal will increase feedwater, potentially compounding the problem. Most boilers do not show appreciable shrink or swell from feedwater because it is heated and drum baffling is used. The level controller will attempt to counteract the effect of the feedforward. The solution in many cases is to filter or delay the feedforward steam signal. This accommodates the change in boiler inventory that is occurring.

Drum level control problems can cause production inef-ficiencies, product quality issues, production limits, and in some cases can even create safety risks. In extreme cases, level control problems have resulted in costs of millions of dollars per year. Proven methods are available to substantially improve drum level control. The control engineer can perform a simple but systematic analysis of the control system to establish the root cause of the con-trol problem and reestablish effective drum level control.

Andrew W. R. Waite is principal process control consul-tant for Emerson Canada.

www.emersonprocess.com

90

80

70

60

50

40

300 100 200 300 400 500 600 700 800

%Sp

an

Time (sec.)

0.0 1750.0 3500.0 5250.0 7000.0SecMean=18.9479 2Sig=3.41 (18%)

Var 04 FI-236-069_A12.PV (Main steam ow)

Steam ow

Output Into manual

15.0018.0021.0024.0027.00

21.0019.0017.0015.0013.00

Mg/hr

Mg/hr

Mean=17.5918 2Sig=4.807 (23.2%)

Var 01 LIC-236-050_PID3.OP (Drum level control_3 element) - Bump MCC0011-027 - LIC-236-050_PID3_PV.dat 05/28/2010 15:24:11

10.005.00

-5.00-10.00

0.00

cm

Mean=0.0592658 2Sig=3.907 (6.59e+003%)

MCC0011-028 - LIC-236-050_PID3_PV.dat 05/28/2010 15:24:11

MCC0011-036 - LIC-236-069_A12_PV.dat 05/28/2010 15:24:11

Level

dX=(5 Sec/Div)900 950800

1311-FT.PV1304-LT.PV

West WHB feedwater owWest WHB level

LUC408AC.dat 12/16/2004LUC408AA.dat 12/16/2004

850 1000 1050 1100 1150 1200Sec

2.000

3.000

4.000

5.000

6.000

50.0046.0042.0038.0034.0030.00

Inch

pph

DY=(0.2 Inch/Div)

DU=(0.8 pph/Div) Bump 01

du

Slope 1 Slope 2Dead time ?

Kp=(slope2-slope1)/du

Figure 12b: Open-loop drum level step test.

Figure 13: Lambda tuning.

Figure 14: Disturbance caused by variation in process steam demand.



Challenges ofMotor Selection and Sizing

The range of sizes, types, and configurations of electric motors can seem endless. Here are a few ideas for navigating the choices.

Example: Driving a chain conveyor with a gear motor and VFD.SEW Eurodrive

Input data: A chain conveyor is to transport wooden boxes up a slope of = 5 at a speed of 0.5 m/s. There is a maximum of four boxes each weighing 500 kg on the

conveyor. The chain itself has a weight of 300 kg. The friction factor between chain and base is specified at = 0.2. A mechanical stop is mounted at the end of the chain conveyor which aligns the boxes before they are pushed onto a second conveyor belt. During this process, the box slides on the chain with a friction factor of = 0.7.

The application calls for a helical-worm gear unit that is frequency-controlled up to approximately 50 Hz.

Velocity: v = 0.5 m/sIncline: = 5Weight of transported material: mL = 2,000 kgWeight of chain: mD = 300 kgFriction factor between chain and base: 1 = 0.2Friction factor between box and chain: 2 = 0.7

Jack Smith

Motors

P aradoxically, electric motors are simple, yet complex. Their simplicity comes from having a single purpose: to convert electrical energy into mechanical energy. Their complexity comes from myriad applications where motors are used. A motors usefulness is in how it is applied. A spinning motor with nothing connected to its shaft is a waste of time, money, and energy.

However, the value of a motor is how efficiently and effectively its mechanical energy operates conveyors, fans, pumps, and other types of industrial equipment. To specify and apply electric motors, engineers must thoroughly understand the electrical and physical characteristics of the motors and the applications in which they are used.

Terms such as torque, horsepower, inertia, friction, acceleration, and load come to mind when designing motorized equipment. And there are formulas that apply to every parameter. For example, the relationship between horsepower, torque, and speed is fairly straightforward and is calculated using simple mathematics:

Horsepower = (torque in pound-feet x motor speed in RPM)/5,250

Torque and speed can be found by changing the formula algebraically. However, nothing happens unless the motor actually starts spinning, which requires it to overcome iner-

tia of both the motor and its load. This is why pre-EPAct (Energy Policy Act of 1992) motors require five or six times their full-load amps (FLA) to come up to speed, and NEMA premium efficiency motors can require eight to 10 times FLA to reach operating speed.

Inertia and friction work together to resist starting a still motor. Although coefficient of friction is another frequently used motor application term, it cant be found through direct calculations; it must be measured experimentally. The ratio of friction force to normal force is a simplified definition of the coefficient of friction.

While the coefficient of friction depends on the proper-ties of two materials that come into contact as with motor shaft and bearings, for example, there are other factors that come into play. Temperature, velocity, atmosphere, shape, and lubrication affect the coefficient of friction as well. Obviously, lowering friction increases motor efficiency.

Motors are used in a plethora of applications. While many books about motor design and applications have been written, they barely scratch the surface of possibili-ties. One of the sidebars with this article gives you an idea of how complex the calculations can be if you want to con-sider all the relevant variables connected to an application. If you read this article online, there is additional detail and a second example.

Jack Smith is an industry consultant and writer, and served as an editor for Plant Engineering. Reach him at [email protected].

AAM1206_Feat03_Motor_V3msFINAL.indd 12 5/29/12 3:02 PM


Desired acceleration: a = 0.25 m/s2Sprocket diameter: D = 250 mmStarting frequency: 10 cycles/hour and 16 hours/day

Calculating the optimum motor size depends on consid-ering all the variables and following the right equations. For example, simply calculating the total resistance that the motor has to overcome involves the weight and friction of the conveyor itself carrying the load, additional friction when a box hits the stop, plus the efficiency of the gear unit itself attached to the motor.

Here is the calculation for determining the resistance force of the conveyor, half the weight of the chain, and the maximum load of boxes:

Here is the calculation for the additional resistance when a box hits the stop:

This is just the beginning since making a complete analysis of the application includes a number of additional factors:

Efficiency of the worm-gear unit External moment of inertia Load torque on the motor Acceleration torque on the motor Conveyor speed relative to motor RPM Gear unit ratio Service factor, and Static power

Ultimately, once the conveyor is built and operating in real-world conditions, it will be a simple task to measure the performance of the motor and verify the accuracy of your starting assumptions.

Read this article online at www.controleng.com to see the full set of calculations for this example and another.

Making good motor decisionsJoe Kimbrell

Correctly sizing an ac motor is important; overloaded motors can overheat and under-loaded motors waste ener-gy. Because a motors energy usage accounts for more than 95% of its lifetime cost, achieving maximum energy efficiency is crucial.

But this doesnt guarantee that the latest highest effi-ciency motor is the best solution for every application. While premium efficiency motors are important, its equally important to size the motor correctly. Otherwise, optimal energy efficiency wont ever be realized. In addition, there are times when older efficiency motors can be rewound and actually improve their efficiency.

Sizing and output speedThe two most important factors when sizing any type of

motor are torque and output speed. Finding the required output speed is relatively easy and can be determined by the design specifications. Determining the correct torque is typically more problematic.

Many motors in use today are oversized as this is often a substitute for more precise up-front engineering. For example, if an application really requires slightly more than 5 hp at infrequent intervals, a 7.5 hp motor is often installed. In this situation, the 7.5 hp motor will definitely work, but it will be running well below full-load torque (fur-ther down the efficiency curve) and wasting a lot of energy.

In applications that only require the motor to operate above full load for short periods of time, a better solution may be to pick the right-size motor with a higher service factor. For example, if a motor has a 1.15 service factor, it can handle an additional 15% load occasionally without damaging the motor.

Conducting a motor surveyThe best way to correctly size a replacement motor is by

conducting a motor survey, which begins by reviewing and cataloging the nameplate information on the current motor to check rated speed, efficiency, full-load current, etc.

Next, monitor the current the motor is drawing by using a clamp-on meter. In most systems, there are many unknown factors, such as friction and mechanical trans-mission efficiencies, which affect motor loading. Therefore, getting an actual measurement of the current going into the motor helps determine the true required motor size needed.

Determining the load requirement accurately is important because motors operate most efficiently near full load. Best efficiency is achieved above 70% of full-load torque. Below 60%, efficiencies start to drop off dramatically.

The motor nameplate is the first step of a motor survey because it supplies valuable information, such as speed rating and full-load current, to help in determining the cor-rect motor size.

AAM1206_Feat03_Motor_V3msFINAL.indd 13 5/29/12 3:02 PM

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There are several websites that pro-vide information on how to determine motor load size, such as the U.S. Dept. of Energy.

http://www1.eere.energy.gov/manufacturing/tech_deployment/pdfs/10097517.pdf

Rewind or replace?If a motor fails before a motor survey

can be performed, examining the age and type of the motor helps to deter-mine if the motor should be repaired or replaced. If the failed motor isnt an EPAct motor, the repair-versus-replace

motors

decision is easy, since the motorshould be replaced in most cases.

If an EPAct motor fails, then rewind-ing should be considered. It used to be that rewinding a motor often meant losing efficiency, but thats no longer the case. In most instances the original motor efficiency can be main-tained. In some cases, the rewound motor can actually achieve increased efficiency. An efficiency discussion with your local motor repair shop can help determine the options. The con-siderations on whether to repair or replace also include the type of motor involved, how often the motor is run-ning, and its efficiency.

If the failed motor is a special or custom motor, additional fac-tors determine whether to repair or replace (longer lead times for custom motors, higher costs, etc.). For many custom motors, rewinding is a more attractive proposition. For standard motors, replacement is often the bet-ter way to go.

If the motor is running constantly, the return on investment (ROI) for a new, premium-efficiency motor will happen faster. If the motor is run spo-radically, then the cost calculations for replacing versus rewinding require more careful analysis. Once again, there are several websites, such as the Department of Energy site listed above, that can help with these cal-culations. The Dept. of Energy also provides a free software package, MotorMaster+, which assists in creat-ing a motor survey and helps with motor repair/replace decisions.

http://www1.eere.energy.gov/manu-facturing/tech_deployment/software_motormaster.html

When trying to cut costs by increas-ing energy efficiency, selecting the right-sized motor is as important as the energy efficiency of the new motor. Conducting a thorough motor survey is the best method for deter-mining the right-size motor, as well as for making the correct replace-versus-rewind decision.

Joe Kimbrell is product manager of drives, motors, and motion for AutomationDirect.

www.automationdirect.com

AAM1206_Feat03_Motor_V3msFINAL.indd 14 5/29/12 3:10 PMPLE120601-SUP1_Ads.indd 14 5/29/2012 5:08:10 PM

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